The Experimental Forecast Program

Tag: Convection Initiation

I am posting late this week. It has been a wild ride in the HWT. The convection initiation desk has been active and Tuesday was no exception. The threat for a tornado outbreak was clear. The questions we faced for forecasting the initiation of storms were:1. What time would the first storms form?2. Where would they be?3. How many episodes would there be?

This last question requires a little explanation. We always struggle with the criteria that denotes convection initiation. Likewise we struggle with how to define the multiple areas and multiple times at which deep moist convection initiates. This type of problem is “eliminated” when you issue a product for a long enough time period. Take the convective outlook for example. Since the risk is defined for the entire convective day you can account for the uncertainty in time by drawing a larger risk area and subsequently refining it. But as you narrow down your time window (from 1 day to 3 hours or even 1 hour) the problems can become significant.

In our case, the issue for the day was compounded because the dryline placement in the models was significantly east of the observed position by the time we started making our forecast. We attempted to account for this fact and as such had to adopt to a feature relative perspective of CI along the dryline. However, the mental picture you are assembling of the CI process (location, timing, number of episodes, number of storms) is tied not just to the boundaries you are considering, but the presumed environment in which they will form.

The feature relative environment then would necessarily be in error because we simply do not have enough observations to account for the model error. We did realize that shallow moisture, which was shown on morning soundings, was not going to be the environment in which our storms formed. Surface dew points were higher and staying near 68 in the warm sector. We later confirmed this with soundings at LMN which showed the moist layer increase in depth with time.

So we knew we had two areas of initial storm formation, one in the panhandle of OK and into KS along the cold front to the west and triple point to the east. The other area was along the dryline in OK and TX. We had to decide how far south storms would initiate. As we figuring all of this out, we had to look at the current satellite imagery since that was the only tool which was accounting for the correct dryline placement and estimate how far east it might travel, or mix out to in order to make the forecast.

Sure enough, the warm sector had multiple cloud streets ahead of the dryline. Our 4km model suite is not really capable of resolving cloud streets but we still needed to make our forecast roughly 1-2 hours before CI. So in a sense we were not making a forecast as much as we were making a longer more uncertain nowcast (probably not abnormal given the inherent unpredictability of warm season convection). Most people put the first storm in KS and would end up being quite accurate in placement. Some of us went ahead of the dryline in west central OK and were also correct.

There was one more episode in southern OK and then another in TX later on. This case will require some careful analysis to verify the forecast, other than subjective assessments. Today we got to see some of the potential objective methods via DTC, showing MODE plots of this case. The object identification of reflectivity via neighborhood and also merging and matching were quite interesting and should foster vigorous discussion.

Last but not least, the number of models we interrogated continued to increase, yet we were feeling confident in understanding this wide variety of models using all of the visualization tools including the more rapid web-based plots, and the use of the sub-hourly convectively active fields. We are getting quite good at distilling information from this very large dataset. There are so many opportunities for quantifying model skill that we will be busy for a long time.

It was interesting to be under the threat of tornadoes and to be in the forecast path of them. It was quite a day, especially since the remnant of the hook echo moved over Norman showering debris over the area picked up from the Goldsby Tornado. The NWC was roughly 3-5 miles away from the dissipation point of that Tornado.

The HWT is examining some fairly sophisticated model simulations over a big domain. One question that frequently arises is: Can we trust the model over here if it is wrong over there?

What does “wrong” mean in these somewhat new models? Wrong in the sense that convection is absent or wrong in the sense that convection is too widespread? Perhaps, a particular feature is moving too slow or too fast. Can you really throw out the whole simulation if a part is “wrong”? Or do you just need time to figure out what is good/bad and extract what you can? Afterall the model is capable of detail that is not available anywhere else. That includes observations.

So Thursday and Friday we discussed how wrong the models have been. The features missed, the features misrepresented, the features absent. Yet each day we were able to extract important information. We were careful about what we should believe. On Friday, though, it was a different story. The NSSL WRF simulated satellite imagery was spot on. That is 14 hours into the simulation where the upper low, its attendant surface cold front were almost identical.

Our domain was northern AR, southern MO, western TN and MS. The models were not in agreement mind you. The different boundary layer schemes clustered into two groups: all the schemes were going for the northern AR initiation, and a second group, the TKE based schemes were also going for the southern part of the cold front. Another signal I was paying attention was post-frontal convergence that was showing up. I made note of it but I never went back to check all the simulations but I wanted to keep that threat in the forecast. Turns out, the TKE schemes hit on all of these features. The northern storms initiated similar to model consensus, the southern storms initiated as well, and so did the secondary episode behind the front (at least from the radar perspective).

The second domain of the day was Savannah GA, in the afternoon. This was an event involving convection possibly moving in from the west, the sea breeze front penetrating far inland along the east, a sea breeze fron the west FL and gulf coast sea breeze penetrating even farther inland, and a highly organized boundary layer sandwiched in between. The models had little in the way of 30 dBz 1km reflectivity at hourly intervals. The new CI algorithms showed that CI was occurring along all of the aforementioned features:1. Along the sea breezes,2. in the boundary layer along horizontal convective rolls,3. along the intersections of 1 and 2,4. and finally along the outflow entering into our domain.

We went for it and there was much rejoicing. We watched all afternoon as those storms developed along radar fine lines, and along the sea breeze. This was a victory for the models. These storms ended up reaching severe levels as a few reports came in.

As far as adding value on days like this, I am less certain. Our value was in extracting information. There is much to add value to. At this stage, we are still learning. It is impossible to draw what the radar will look like in 3 hours (unless there is nothing there). But I think as we assemble the capabilities of these models, we will be able to visualize what the radar might look like. As our group discussed, convection in the atmosphere appears random. But only because we have never seen the underlying organization.

It is elusive because our observing systems do not see uniformly. We see vertical profiles, time series at a location, and snap shots of clouds. We see wind velocity coming towards or away from radars. We see bugs caught in convergence lines (radar fine lines). So these models provide a new means to see. Maybe we see things we know are there. Maybe we are seeing new things that we don’t even know to look for. Since we can not explain them we are not looking for them. We expect to see more cool stuff this week.

Thanks to all the forecasters this week who both endured us trying to figure out our practical, time limited forecast product, and who taught us how to interrogate their unique tools and visualizations. We begin anew tomorrow with a whole new crop of people, a little better organized, with more new stuff on display, and more complex forecasts to issue.

As expected, it was quite a challenge to pick domains for days 2 and 3. Day 2 was characterized by 3 potential areas of CI: Ohio to South Carolina, Minnesota and Iowa, and Texas. We were trying to determine how to deal with pre-existing convection: whether it was in our domain already or would be in our domain during our assumed CI time. As a result, we determined that the Ohio to South Carolina domain was not going to be as clean-slate as Texas or Minnesota. So we voted out SC.

We were left with Texas (presumed dryline CI) and Minnesota (presumed warm front/occlusion zone). Texas was voted in first but we ended up making the MN forecast in the afternoon. Data for this day did not flow freely, so we used whatever was available (NSSL-WRF, operational models, etc).

The complication for TX was an un-initialized short wave trough emanating from the subtropical jet across Mexico and moving northward. This feature was contributing to a north to south band of precipitation and eventually triggered a storm in central and eastern OK, well to the east of our domain. The NSSL WRF did not produce the short wave trough and thus evolved eastern TX much differently than what actually occurred despite having the subtropical jet in that area. So we were gutsy in picking this domain despite this short wave passing through our area. We were still thinking that the dryline could fire later on but once we completed our spatial confidence forecast (a bunch of 30 percents and one 10 percent) and our timing confidence (~+/- 90 minutes) it was apparent we were not very confident.

This was an acceptable challenge as we slowly began to assemble our spatial forecast, settling on a 3 hour period in which we restrict ourselves to worrying only about new, fresh convection by spatially identifying regions within our domain where convection is already present. This way we don’t have to worry about secondary convection directly related to pre-existing convection. We also decided that every forecaster would enter a spot on the map where they thought the first storms would develop (within 25 miles of their point). This makes the forecast fun and competitive and gets everyone thinking not just about a general forecast but about the scenario (or scenarios if there are multiple in the domain).

The next stop on this days adventure was MN/IA/Dakotas. This was challenging for multiple reasons:1. The short wave trough moving north into OK/KS and its associated short wave ridge moving north northeast2. the dryline and cold front to the west of MN/IA,3. the cold upper low in the Dakotas moving east north east.

The focus was clear and the domain was to be RWF. This time we used a bigger domain in acknowledgement of the complex scenario that could unfold. You had the model initiating convection along the warm front, along the cold front in NE on a secondary moisture surge associated with the short wave trough, and a persistent signal of CI over Lake Superior (which we ignored).

We ended up drawing a rather large slight risk extending down into IA and NE from the main lobe in MN with a moderate area extending from south central MN into northern IA. After viewing multiple new products including simulated satellite imagery (water vapor and band differencing from the NSSL WRF and the Nearcast moisture and equivalent potential temperature difference, it was decided that CI was probably with everyone going above 50 percent confidence.

In Minnesota we did quite well, both by showing a gap near Omaha where the moist surge was expected but did not materialize until after our 0-3 UTC time period. Once the moisture arrived … CI. In MN CI began just prior to 23 UTC encompassing some of our moderate risk even down into IA, yet these “Storms” in IA were part of the CI episode but would not be objectively classified as storms from a reflectivity and lifetime perspective, but they did produce lightning.

The verification for Texas was quite bad. Convection formed to the east early, and to the west much later than anticipated associated with a southern moisture surge into NM from the upper level low migrating into the area nearly 11 hours after our forecast period start.

As it turns out, we awoke this morning to a moderate risk area in OK, but the NM convection was totally missed by the majority of model guidance! The dryline was in Texas still but now this convection was moving toward our CDS centerpoint and we hoped that the convection would move east. A review of the ensemble indicated some members had some weak signals of this convection, but it became obvious that it was not the same. We did key in on the fact that despite the missed convection in the TX panhandle the models were persistent in secondary initiation despite the now-developing convection in southern TX. We outlooked the area around western OK and parts of TX.

In the afternoon, we looked in more detail at the simulated satellite imagery, nearcast, and the CIRA CI algorithm for an area in and around Indiana. This was by far the most complicated and intellectually stimulating area. We analyzed the ensemble control member for some new variables that we output near the boundary layer top (1.2 km AGL roughly): WDT: the number of time steps in the last hour where w exceeded 0.25 m/s and convergence . We could see some obvious boundaries as observed, with a unique perspective on warm sector open celled convection.

In addition we used the 3 hour probabilities of CI that have been developed specifically for CI since these match our chosen 3 hour time periods. We have noticed significant areal coverage from the ensemble probabilities which heavily weight the pre-existing convection CI points. Thus it has been difficult to assign the actual new CI probabilities since we cant distinguish the probability fields if two close proximity CI events are in the area around where we wish to forecast. That being said, we have found them useful in these messy situations. We await a clean day to see how much a difference that makes.

What a great start to the HWT. There were troubles, and troubleshooters. We had plenty of forecasters and plenty of forecast problems. All in all it was quite a challenge.

The convection initiation (CI) team had some great discussion on the CI definition including all the ways in which CI gets complicated. For example, visually we can identify individual clouds, or cloud areas on satellite. When using radar, we might select areas of high reflectivity that last for say 30 minutes. In the NWP models, we rely on quantitative values at a single grid point at two instances in time.

We also have the issue of whether CI is part of a larger episode (close in space and/or time by other storms) or developing as a direct result of previous convection (ahead of a squall line). In these relative cases, visually identifying new storms might be easily accomplished, but in the model atmosphere (in a grid point centric algorithm) new CI points may be all over the place, say as gravity waves or outflow achieve just enough separation to be classified as new (thus CI) even though it might simple be redevelopment. From a probability standpoint, spatial probabilities of CI may thus be larger around existing convection. Does this enhanced probability, ahead of the line, signal actual new storm development?

Trying to establish an apples to apples comparison between model and human forecasts of such discrete events is a major challenge. We are testing 3 model definitions of CI to see their viability from the perspective of forecasters, and we will also evaluate object based approaches to CI.

Of course we cannot talk about where CI might be without talking about when! When will the first storm form? This gets back to your definition of CI. Should the storm produce lightning to be classified a storm? How about reaching a threshold reflectivity? How about requiring it that it last a certain amount of time? The standard definition of storms relies on its mode (ordinary, multicell, supercell); all having a unique evolution with the placement of the updraft and precipitation fall out. But what about storm intensity (however you define it)?

I should also acknowledge that defining all of this can be quite subjective and is relevant to individual users of a CI forecast. So we are definition dependent, but most people know it when they see it. Lets consider two viewpoints: The severe storm forecaster and an aviation forecaster. The severe storm forecaster wants to know about where and when a storm may form so they can decide the potential threat thus leading to a product (mesoscale discussion for specific hail, wind, tornado threats) provided that storm or CI episode is long lived. The aviation forecaster might be concerned with the sudden appearance of cumulonimbus which could pose an immediate threat to aircraft. But they are also concerned with the resulting coverage of new storms (diverting traffic, shutting down airports, planning new traffic routes or patterns) and the motion, expansion, and decay of existing storms.

And lastly it will be important for us to establish what skill the models and forecasters have with respect to CI. This is not a new area of study, but it is one where lots of complexity, vagaries of definitions, and also a lack of understanding contribute to making this one of the greatest forecast challenges.

As we refine what our forecast will consist of, we will report back on how our forecast product evolved. The more we forecast, the more we learn.